ASF-funded research published in the Journal of Neurodevelopmental Disorders has identified that delta—a frequency of brain rhythms identifiable by EEG scans—can serve as a reliable biomarker for pre-clinical and clinical trials in Angelman syndrome. The research team, led by Dr. Mike Sidorov at the University of North Carolina-Chapel Hill, compared existing EEG data from the Angelman Syndrome Natural History Study to neuro-typical EEG data from Massachusetts General Hospital. The study showed that delta abnormalities can be seen across the brain of children with Angelman syndrome, and during both sleep and wake.
“We focused on delta because it is the most commonly reported abnormality in AS EEG scans,” said Sidorov. “In doing so, we consistently found that nearly every individual with AS has increased delta compared to neuro-typical individuals.” Most importantly, we found that delta abnormalities can be quantified, said Sidorov. “By reducing delta to a single number, we are able to track it reliably over time within individuals. We were thrilled with the result and believe delta has great potential for use as a biomarker and outcome measure in future clinical trials, as well as pre-clinical studies because we saw the same result in our mouse-model data.”
Few authentic biomarkers for Angelman syndrome have been found. Biomarkers must be objective, reliable, and repeatable in different settings in order to accurately determine whether a potential therapeutic is effective. This latest discovery checks all of those boxes. This ASF-funded published research takes a significant step forward in having viable tools to measure the success of pre-clinical and clinical drug trials.